Managing Error Recovery Data in a Dispersed Storage Network

ABSTRACT

A method for managing error recovery data in a dispersed storage network begins with a storage network processing module receiving a write request for an encoded data slice of a set of encoded data slices, where data is dispersed in accordance with dispersed error encoding parameters to produce a set of encoded data slices. The method continues with the storage network processing module generating parity data for the encoded data slice and sending the encoded data slice to a first storage unit of a set of storage units. Finally, the method continues with the storage network processing module sending the parity data for the encoded data slice to a second storage unit of a set of storage units.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. § 120 as a continuation of U.S. Utility application Ser. No.16/200,103, entitled “SELECTIVE GENERATION OF SECURE SIGNATURES IN ADISTRIBUTED STORAGE NETWORK”, filed Nov. 26, 2018, which is acontinuation-in-part of U.S. Utility application Ser. No. 15/824,651,entitled “MAINTAINING REFERENCES TO RELATED OBJECTS IN A DISTRIBUTEDSTORAGE NETWORK”, filed Nov. 28, 2017, which is a continuation-in-partof U.S. Utility application Ser. No. 14/147,982, entitled “GENERATING ASECURE SIGNATURE UTILIZING A PLURALITY OF KEY SHARES”, filed Jan. 6,2014, issued as U.S. Pat. No. 9,894,151 on Feb. 13, 2018, which is acontinuation of U.S. Utility patent application Ser. No. 13/413,232,entitled “GENERATING A SECURE SIGNATURE UTILIZING A PLURALITY OF KEYSHARES,” filed Mar. 6, 2012, issued as U.S. Pat. No. 8,627,091 on Jan.7, 2014, which claims priority pursuant to 35 U.S.C. § 119(e) to U.S.Provisional Application No. 61/470,524, entitled “ENCODING DATA STOREDIN A DISPERSED STORAGE NETWORK,”, filed Apr. 1, 2011, all of which arehereby incorporated herein by reference in their entirety and made partof the present U.S. Utility Patent Application for all purposes.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not applicable.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersing error encoded data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data in accordance with the present invention;

FIG. 4 is a schematic block diagram of a generic example of an errorencoding function in accordance with the present invention;

FIG. 5 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present invention;

FIG. 6 is a schematic block diagram of an example of a slice name of anencoded data slice (EDS) in accordance with the present invention;

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of data in accordance with the present invention;

FIG. 8 is a schematic block diagram of a generic example of an errordecoding function in accordance with the present invention;

FIG. 9A is a flowchart illustrating an example of storing key shares inaccordance with the present invention;

FIG. 9B is a diagram illustrating an example of a key share storagetable in accordance with the present invention;

FIG. 9C is a flowchart illustrating an example of generating a signaturein accordance with the present invention;

FIG. 9D is a flowchart illustrating an example of generating a signaturecontribution in accordance with the present invention; and

FIG. 10 is a flowchart illustrating another example of generating asignature contribution in accordance with the invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) 10 that includes a plurality ofcomputing devices 12-16, a managing unit 18, an integrity processingunit 20, and a DSN memory 22. The components of the DSN 10 are coupledto a network 24, which may include one or more wireless and/or wirelined communication systems; one or more non-public intranet systemsand/or public internet systems; and/or one or more local area networks(LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of storage units 36 that may belocated at geographically different sites (e.g., one in Chicago, one inMilwaukee, etc.), at a common site, or a combination thereof. Forexample, if the DSN memory 22 includes eight storage units 36, eachstorage unit is located at a different site. As another example, if theDSN memory 22 includes eight storage units 36, all eight storage unitsare located at the same site. As yet another example, if the DSN memory22 includes eight storage units 36, a first pair of storage units are ata first common site, a second pair of storage units are at a secondcommon site, a third pair of storage units are at a third common site,and a fourth pair of storage units are at a fourth common site. Notethat a DSN memory 22 may include more or less than eight storage units36. Further note that each storage unit 36 includes a computing core (asshown in FIG. 2, or components thereof) and a plurality of memorydevices for storing dispersed error encoded data.

Each of the computing devices 12-16, the managing unit 18, and theintegrity processing unit 20 include a computing core 26, which includesnetwork interfaces 30-33. Computing devices 12-16 may each be a portablecomputing device and/or a fixed computing device. A portable computingdevice may be a social networking device, a gaming device, a cell phone,a smart phone, a digital assistant, a digital music player, a digitalvideo player, a laptop computer, a handheld computer, a tablet, a videogame controller, and/or any other portable device that includes acomputing core. A fixed computing device may be a computer (PC), acomputer server, a cable set-top box, a satellite receiver, a televisionset, a printer, a fax machine, home entertainment equipment, a videogame console, and/or any type of home or office computing equipment.Note that each of the managing unit 18 and the integrity processing unit20 may be separate computing devices, may be a common computing device,and/or may be integrated into one or more of the computing devices 12-16and/or into one or more of the storage units 36.

Each interface 30, 32, and 33 includes software and hardware to supportone or more communication links via the network 24 indirectly and/ordirectly. For example, interface 30 supports a communication link (e.g.,wired, wireless, direct, via a LAN, via the network 24, etc.) betweencomputing devices 14 and 16. As another example, interface 32 supportscommunication links (e.g., a wired connection, a wireless connection, aLAN connection, and/or any other type of connection to/from the network24) between computing devices 12 and 16 and the DSN memory 22. As yetanother example, interface 33 supports a communication link for each ofthe managing unit 18 and the integrity processing unit 20 to the network24.

Computing devices 12 and 16 include a dispersed storage (DS) clientmodule 34, which enables the computing device to dispersed storage errorencode and decode data (e.g., data 40) as subsequently described withreference to one or more of FIGS. 3-8. In this example embodiment,computing device 16 functions as a dispersed storage processing agentfor computing device 14. In this role, computing device 16 dispersedstorage error encodes and decodes data on behalf of computing device 14.With the use of dispersed storage error encoding and decoding, the DSN10 is tolerant of a significant number of storage unit failures (thenumber of failures is based on parameters of the dispersed storage errorencoding function) without loss of data and without the need for aredundant or backup copies of the data. Further, the DSN 10 stores datafor an indefinite period of time without data loss and in a securemanner (e.g., the system is very resistant to unauthorized attempts ataccessing the data).

In operation, the managing unit 18 performs DS management services. Forexample, the managing unit 18 establishes distributed data storageparameters (e.g., vault creation, distributed storage parameters,security parameters, billing information, user profile information,etc.) for computing devices 12-14 individually or as part of a group ofuser devices. As a specific example, the managing unit 18 coordinatescreation of a vault (e.g., a virtual memory block associated with aportion of an overall namespace of the DSN) within the DSN memory 22 fora user device, a group of devices, or for public access and establishesper vault dispersed storage (DS) error encoding parameters for a vault.The managing unit 18 facilitates storage of DS error encoding parametersfor each vault by updating registry information of the DSN 10, where theregistry information may be stored in the DSN memory 22, a computingdevice 12-16, the managing unit 18, and/or the integrity processing unit20.

The managing unit 18 creates and stores user profile information (e.g.,an access control list (ACL)) in local memory and/or within memory ofthe DSN memory 22. The user profile information includes authenticationinformation, permissions, and/or the security parameters. The securityparameters may include encryption/decryption scheme, one or moreencryption keys, key generation scheme, and/or data encoding/decodingscheme.

The managing unit 18 creates billing information for a particular user,a user group, a vault access, public vault access, etc. For instance,the managing unit 18 tracks the number of times a user accesses anon-public vault and/or public vaults, which can be used to generate aper-access billing information. In another instance, the managing unit18 tracks the amount of data stored and/or retrieved by a user deviceand/or a user group, which can be used to generate a per-data-amountbilling information.

As another example, the managing unit 18 performs network operations,network administration, and/or network maintenance. Network operationsincludes authenticating user data allocation requests (e.g., read and/orwrite requests), managing creation of vaults, establishingauthentication credentials for user devices, adding/deleting components(e.g., user devices, storage units, and/or computing devices with a DSclient module 34) to/from the DSN 10, and/or establishing authenticationcredentials for the storage units 36. Network administration includesmonitoring devices and/or units for failures, maintaining vaultinformation, determining device and/or unit activation status,determining device and/or unit loading, and/or determining any othersystem level operation that affects the performance level of the DSN 10.Network maintenance includes facilitating replacing, upgrading,repairing, and/or expanding a device and/or unit of the DSN 10.

The integrity processing unit 20 performs rebuilding of ‘bad’ or missingencoded data slices. At a high level, the integrity processing unit 20performs rebuilding by periodically attempting to retrieve/list encodeddata slices, and/or slice names of the encoded data slices, from the DSNmemory 22. For retrieved encoded slices, they are checked for errors dueto data corruption, outdated version, etc. If a slice includes an error,it is flagged as a ‘bad’ slice. For encoded data slices that were notreceived and/or not listed, they are flagged as missing slices. Badand/or missing slices are subsequently rebuilt using other retrievedencoded data slices that are deemed to be good slices to produce rebuiltslices. The rebuilt slices are stored in the DSN memory 22.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSN interface module 76.

The DSN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). The DSNinterface module 76 and/or the network interface module 70 may functionas one or more of the interface 30-33 of FIG. 1. Note that the IO deviceinterface module 62 and/or the memory interface modules 66-76 may becollectively or individually referred to as IO ports.

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data. When a computing device 12 or 16 has data tostore it disperse storage error encodes the data in accordance with adispersed storage error encoding process based on dispersed storageerror encoding parameters. The dispersed storage error encodingparameters include an encoding function (e.g., information dispersalalgorithm, Reed-Solomon, Cauchy Reed-Solomon, systematic encoding,non-systematic encoding, on-line codes, etc.), a data segmentingprotocol (e.g., data segment size, fixed, variable, etc.), and per datasegment encoding values. The per data segment encoding values include atotal, or pillar width, number (T) of encoded data slices per encodingof a data segment (i.e., in a set of encoded data slices); a decodethreshold number (D) of encoded data slices of a set of encoded dataslices that are needed to recover the data segment; a read thresholdnumber (R) of encoded data slices to indicate a number of encoded dataslices per set to be read from storage for decoding of the data segment;and/or a write threshold number (W) to indicate a number of encoded dataslices per set that must be accurately stored before the encoded datasegment is deemed to have been properly stored. The dispersed storageerror encoding parameters may further include slicing information (e.g.,the number of encoded data slices that will be created for each datasegment) and/or slice security information (e.g., per encoded data sliceencryption, compression, integrity checksum, etc.).

In the present example, Cauchy Reed-Solomon has been selected as theencoding function (a generic example is shown in FIG. 4 and a specificexample is shown in FIG. 5); the data segmenting protocol is to dividethe data object into fixed sized data segments; and the per data segmentencoding values include: a pillar width of 5, a decode threshold of 3, aread threshold of 4, and a write threshold of 4. In accordance with thedata segmenting protocol, the computing device 12 or 16 divides the data(e.g., a file (e.g., text, video, audio, etc.), a data object, or otherdata arrangement) into a plurality of fixed sized data segments (e.g., 1through Y of a fixed size in range of Kilobytes to Terabytes or more).The number of data segments created is dependent of the size of the dataand the data segmenting protocol.

The computing device 12 or 16 then disperse storage error encodes a datasegment using the selected encoding function (e.g., Cauchy Reed-Solomon)to produce a set of encoded data slices. FIG. 4 illustrates a genericCauchy Reed-Solomon encoding function, which includes an encoding matrix(EM), a data matrix (DM), and a coded matrix (CM). The size of theencoding matrix (EM) is dependent on the pillar width number (T) and thedecode threshold number (D) of selected per data segment encodingvalues. To produce the data matrix (DM), the data segment is dividedinto a plurality of data blocks and the data blocks are arranged into Dnumber of rows with Z data blocks per row. Note that Z is a function ofthe number of data blocks created from the data segment and the decodethreshold number (D). The coded matrix is produced by matrix multiplyingthe data matrix by the encoding matrix.

FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encodingwith a pillar number (T) of five and decode threshold number of three.In this example, a first data segment is divided into twelve data blocks(D1-D12). The coded matrix includes five rows of coded data blocks,where the first row of X11-X14 corresponds to a first encoded data slice(EDS 1_1), the second row of X21-X24 corresponds to a second encodeddata slice (EDS 2_1), the third row of X31-X34 corresponds to a thirdencoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to afourth encoded data slice (EDS 4_1), and the fifth row of X51-X54corresponds to a fifth encoded data slice (EDS 5_1). Note that thesecond number of the EDS designation corresponds to the data segmentnumber.

Returning to the discussion of FIG. 3, the computing device also createsa slice name (SN) for each encoded data slice (EDS) in the set ofencoded data slices. A typical format for a slice name 80 is shown inFIG. 6. As shown, the slice name (SN) 80 includes a pillar number of theencoded data slice (e.g., one of 1-T), a data segment number (e.g., oneof 1-Y), a vault identifier (ID), a data object identifier (ID), and mayfurther include revision level information of the encoded data slices.The slice name functions as, at least part of, a DSN address for theencoded data slice for storage and retrieval from the DSN memory 22.

As a result of encoding, the computing device 12 or 16 produces aplurality of sets of encoded data slices, which are provided with theirrespective slice names to the storage units for storage. As shown, thefirst set of encoded data slices includes EDS 1_1 through EDS 5_1 andthe first set of slice names includes SN 1_1 through SN 5_1 and the lastset of encoded data slices includes EDS 1_Y through EDS 5_Y and the lastset of slice names includes SN 1_Y through SN 5_Y.

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of a data object that was dispersed storage error encodedand stored in the example of FIG. 4. In this example, the computingdevice 12 or 16 retrieves from the storage units at least the decodethreshold number of encoded data slices per data segment. As a specificexample, the computing device retrieves a read threshold number ofencoded data slices.

To recover a data segment from a decode threshold number of encoded dataslices, the computing device uses a decoding function as shown in FIG.8. As shown, the decoding function is essentially an inverse of theencoding function of FIG. 4. The coded matrix includes a decodethreshold number of rows (e.g., three in this example) and the decodingmatrix in an inversion of the encoding matrix that includes thecorresponding rows of the coded matrix. For example, if the coded matrixincludes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2,and 4, and then inverted to produce the decoding matrix.

FIG. 9A is a flowchart illustrating an example of storing key shares.FIG. 9A is a flowchart illustrating an example of storing key shares.Storage of secrets in multiple storage nodes can be used to prevent thecapture of the ciphertext and the subsequent cryptanalysis on thatciphertext. In such a system decrypting an encrypted message or signinga message involves several parties (more than some threshold number) whomust cooperate in the decryption or signature protocol. In an example, amessage is encrypted using a public key and the corresponding privatekey is shared among the participating parties. Multiple schemes andalgorithms are available for implementing these “threshold signature”cryptosystems. For example, one such system is based on distributingsecret shares of a private key (see, for example, “Practical ThresholdSignatures” by Victor Shoup, et. al). Another example is based on theBoneh-Lynn-Shacham (BLS) Signature Scheme (using threshold signaturesbased on bi-linear pairings). Yet another example is the variousthreshold signature schemes where shares are produced from linearfunctions applied to a private key. Many more examples will be readilyapparent to those skilled in the related technology space. In anexample, some signature are algorithms distinct fromRivest-Shamir-Adleman (RSA) type cryptosystems.

In many of the systems referred to above the participants/nodes need notbe pre-established before the threshold cryptosystem(s) are employed.Instead, a single share value generated from a key is sufficient to beused with virtually any combination of servers used to produce aparticular signature.

The method begins with step 144 where a processing module determines aprivate key (e.g., an encryption key d utilized in an encryptionalgorithm). Such a determination may be based on one or more ofgenerating a key pair (e.g., a private key and a key), receiving theprivate key, a query, a lookup, and a user input. The method continuesat step 146 where the processing module determines sharing functionparameters. Such sharing function parameters includes one or more of awidth (e.g., a number of storage nodes w), a decode threshold (e.g., anumber of key shares k), a number of shares sets (e.g., w choose k), apublic modulus n, security function constants p and q (e.g., largeprimes such that p*q=n), an encryption algorithm identifier, and adecryption algorithm identifier. Such a determination may be based onone or more of a list, a predetermination, a query, a performance levelindicator, a reliability level requirement, a message, and a command.For example, the processing module determines w=4, k=2, a number ofshares sets=(4 choose 2)=6, a value for n, and a value for p based on alookup and generates a value for q in accordance with p*q=n.

The method continues at step 148 where the processing module determinesa plurality of storage nodes for storing key shares. Such plurality ofstorage nodes includes two or more of a user device, a dispersed storage(DS) unit, a storage server, and a memory device. Such a determinationmay be based on one or more of the sharing function parameters, a list,a predetermination, a query, a performance level indicator, a message,and a command. For example, the processing module determines theplurality of storage nodes to include 4 DS units when the sharingfunction parameters include a width w=4 and a performance levelindicator indicates that a performance level of the 4 DS units comparesfavorably to a performance level threshold.

The method continues at step 150 where the processing module generatesone or more sets of key shares to include the number of shares sets. Forexample, the processing module generates 6 sets of key shares when thewidth=4 and the decode threshold k=2 (e.g., 4 choose 2=6). Such ageneration produces a set of key shares for each combination of a decodethreshold k number of key shares stored in the width w number of storagenodes. Such generation of each set of key shares includes generation inaccordance with a formula (x+y+z) mod Φ(n)=private key d, whereinΦ(n)=(p−1)*(q−1), and x, y, z represent key shares of a correspondingkey share set when a number of key shares is three. For example, theprocessing module randomly chooses values for key shares y and z of acorresponding key share set and generates a value for key share x inaccordance with the formula.

In an example of generating key share sets, the processing modulegenerates 10 key shares sets to include a first key share set thatincludes a key share x1 to store in DS unit 1, a key share yl to storein DS unit 2, and a key share z1 to store in DS unit 3, a second keyshare set that includes a key share x2 to store in DS unit 1, a keyshare y2 to store in DS unit 2, and a key share z2 to store in DS unit4, a third key share set that includes a key share x3 to store in DSunit 1, a key share y3 to store in DS unit 2, and a key share z3 tostore in DS unit 5, a fourth key share set that includes a key share x4to store in DS unit 1, a key share y4 to store in DS unit 3, and a keyshare z4 to store in DS unit 5, a fifth key share set that includes akey share x5 to store in DS unit 1, a key share y5 to store in DS unit4, and a key share z5 to store in DS unit 5, a sixth key share set thatincludes a key share x6 to store in DS unit 2, a key share y6 to storein DS unit 3, and a key share z6 to store in DS unit 4, a seventh keyshare set that includes a key share x7 to store in DS unit 2, a keyshare y7 to store in DS unit 3, and a key share z7 to store in DS unit5, an eighth key share set that includes a key share x8 to store in DSunit 2, a key share y7 to store in DS unit 4, and a key share z7 tostore in DS unit 5, a ninth key share set that includes a key share x9to store in DS unit 3, a key share y9 to store in DS unit 4, and a keyshare z9 to store in DS unit 5, and a 10th key share set that includes akey share x10 to store in DS unit 1, a key share y10 to store in DS unit3, and a key share z10 to store in DS unit 4 when a number storage nodesis 5 and a decode threshold is 3.

The method continues at step 152 where the processing module outputs theone or more sets of key shares to the plurality of storage nodes. Inaddition, the processing module may output one or more of the sharingfunction parameters to each storage node of the plurality of storagenodes. For example, the processing module sends the public modulus n toeach storage node of the plurality of storage nodes. The methodcontinues at step 154 where the processing module destroys the privatekey d. Note that such destroying of the private key may provide thesystem with a security performance improvement. A method to generate asignature based on stored shared keys is described in greater detailwith reference to FIG. 9C. A method to generate a signature contribution(e.g., by a storage node) is described in greater detail with referenceto FIG. 9D.

FIG. 9B is a diagram illustrating an example of a key share storagetable 156 that includes a share set field 158, a node combination field160, and a key share per storage node field 162. Such a share set field158 includes a share sets number of share set identifiers ofcorresponding key share sets. For example, the share set field 158includes 6 share set identifiers 1-6 when a number of storage nodes w=4,a decode threshold k=2, and the share sets number of share setidentifiers is w choose k (e.g., 4 choose 2=6). Such a node combinationfield 160 includes a share sets number of node combination entries,wherein each node combination entry corresponds to a combination of adecode threshold number of storage node identifiers. For example, thenode combination field 160 includes 6 node combination entries includingA-B, A-C, A-D, B-C, B-D, and C-D when storage nodes A-D are utilized tostore a share sets number (e.g., 6) of a decode threshold number (e.g.,2) of key shares.

Such a key share per storage node field 162 includes a share sets numberof storage node fields, wherein each storage node field corresponds to astorage node of a number of storage nodes w utilized to store the keyshares. Each storage node field includes a key share identifier utilizedto identify a key share of an associated share set that is stored in astorage node corresponding to the storage node field. For example, shareset 1 includes utilization of storage node combination A-B such that keyshare x1 is stored in storage unit A and key share y1 is stored instorage node B, share set 2 includes utilization of storage nodecombination A-C such that key share x2 is stored in storage unit A andkey share y2 is stored in storage node C, share set 3 includesutilization of storage node combination A-D such that key share x3 isstored in storage unit A and key share y3 is stored in storage node D,share set 4 includes utilization of storage node combination B-C suchthat key share x4 is stored in storage unit B and key share y4 is storedin storage node C, share set 5 includes utilization of storage nodecombination B-D such that key share x5 is stored in storage unit B andkey share y5 is stored in storage node D, and share set 6 includesutilization of storage node combination C-D such that key share x6 isstored in storage unit C and key share y6 is stored in storage node D.Each set of key shares may be generated in accordance with a formula(x+y) mod Φ(n)=private key d, wherein Φ(n)=(p−1)*(q−1). For example, avalue of key share y1 is chosen randomly and a value for key share x1 isgenerated in accordance with the formula.

FIG. 9C is a flowchart illustrating an example of generating asignature, which include similar steps to FIG. 9A. The method beginswith step 170 where a processing module obtains a message to sign. Sucha message may include a data file, data object, a data file hash, a dataobject cache, a data block, and a hash of a data block, a hash of apayload. Such a payload may include one or more of registry information,key information, encryption algorithm information, a device certificate,a user certificate, and a system element identifier (ID). The methodcontinues with step 172 where the processing module determines sharingfunction parameters.

The method continues at step 174 where the processing module determinesa candidate plurality of storage nodes for retrieving signaturecontributions. Such a determination may be based on one or more of alist of storage nodes utilized to store key shares, a lookup, a command,a query, and a message. The method continues at step 176 where theprocessing module selects a storage node group of the candidateplurality of storage nodes for retrieving signature contributions. Sucha storage node group includes at least a decode threshold number ofstorage nodes. Such a determination may be based on one or more of astorage node status indicator, a storage node performance levelindicator, a retrieval history indicator, a security indicator, a query,a command, a key share storage table lookup, and a message. For example,the processing module determines the storage node group to includestorage nodes A and D based on the key share storage table lookup and aretrieval history indicator for storage nodes A and D that indicates afavorable retrieval history level.

The method continues at step 178 where the processing module outputs aplurality of signature contribution requests to the storage node group.Such a request of the plurality requests may include one or more of ashare set ID, a storage node group ID, the message to sign, and at leastone parameter of the sharing function parameters. For example, theprocessing module outputs signature contribution requests to storagenodes A and B, wherein each signature contribution request includes ashare set ID of A-D, a public modulus n, and a message to sign thatincludes a hash of a device certificate.

The method continues at step 180 where the processing module receivesone or more signature contributions. The method continues at step 182where the processing module determines whether all of a decode thresholdnumber of signature contributions has been received. The method repeatsback to step 176 where the processing module selects the storage nodegroup when the processing module determines that all of the decodethreshold number of signature contributions has not been received. Themethod continues to step 182 when the processing module determines thatall of the decode threshold number of signature contributions has beenreceived. In step 184 the processing module generates a signature basedon the signature contributions. Such generation includes generating thesignature in accordance with the formula signature s=((signaturecontribution A)*(signature contribution B)) mod n, when the decodethreshold is 2 and signature contributions A and B have been received(e.g., from storage nodes A and B). In addition, the processing modulemay verify the signature. Such verification includes decrypting thesignature utilizing an associated public key to produce a decryptedsignature and comparing the decrypted signature to the message to sign(e.g., the hash of the device certificate). The processing moduledetermines that the signature is valid when the comparisons favorable(e.g., substantially the same). The method repeats back to step 176where the processing module selects a storage node group to select adifferent storage node group and repeat the process to re-generate thesignature when the processing module determines that the signature isnot valid.

FIG. 9D is a flowchart illustrating an example of generating a signaturecontribution. The method begins with step 186 where a processing modulereceives a signature contribution request. The method continues at step188 where the processing module retrieves a key share based on sharingfunction parameters. The processing module obtains the sharing functionparameters based on one or more of receiving the sharing functionparameters, extracting the sharing function parameters from the request,a lookup, a message, a command, and a predetermination. For example, theprocessing module extracts the sharing function parameters from thesignature contribution request to include a key share ID. Suchretrieving of the key share includes obtaining the key share ID andretrieving the key share based on the key share ID. For example, theprocessing module obtains key share ID x3, determines a storage node Amemory location based on the key share ID x3, and retrieves the keyshare x3 from a memory of the storage node at the storage node memorylocation.

As another example, the processing module extracts the sharing functionparameters from the signature contribution request to include a shareset ID. Such retrieving of the key share includes obtaining the shareset ID and retrieving the key share based on the share set ID and a keyshare storage table lookup. For example, the processing module obtainsshare set ID A-D, determines a key share ID of x3 based on a key sharestorage table lookup utilizing the share set ID A-D as an index,determines a storage node A memory location based on the key share IDx3, and retrieves the key share x3 from a memory of the storage node atthe storage node memory location.

The method continues at step 190 where the processing module generates asignature contribution based on the key share and a message to sign m.Obtaining the message to sign m includes at least one of extracting themessage to sign m from the signature contribution request and generatinga hash of a payload from the signature contribution request. Suchgeneration of the signature contribution includes generating thesignature contribution in accordance with the formula signaturecontribution=mx mod n. For example, the processing module generates thesignature contribution in accordance with signature contribution A=mx3mod n, when the processing module is associated with storage node A andthe key share is x3. The method continues at step 192 where theprocessing module outputs the signature contribution.

FIG. 10 is a flowchart illustrating another example of generating asignature contribution, which include steps similar to FIG. 9D. Themethod begins with step 200 where a processing module receives asignature contribution request that includes a payload. The methodcontinues at step 202 where the processing module logs the signaturecontribution request. Such logging includes extracting requestinformation from the signature contribution request, obtaining a useridentifier (ID), obtaining a vault ID, obtaining a timestamp,aggregating the request information, the user ID, the vault ID, and thetimestamp to produce logging information, and facilitating storing ofthe logging information.

The method continues at step 204 where the processing module determineswhether timing of the signature contribution request compares favorablyto a timing template. For example, the processing module determines thatthe comparison is favorable when a difference between the timestampassociated with the signature contribution request and a timestampassociated with a previous signature contribution request is greaterthan a time threshold of the timing template. The method branches tosteps 204 where the processing module determines whether the requestcompares favorably to a functionality template, and when the processingmodule determines that the timing of the request does not comparefavorably to the timing template the method continues to step 206 whenthe processing module determines that the timing of the request comparesunfavorably to the timing template. The method continues at step 212where the processing module outputs a request rejection message. Such arequest rejection message includes one or more of the signaturecontribution requests, the logging information, the timestamp associatedwith the signature contribution request, and an error code. Theprocessing module may output the request rejection message to one ormore of a requester, a dispersed storage (DS) imaging unit, a DSprocessing unit, a DS unit, and a user device.

The method continues at step 208 where the processing module determineswhether the signature contribution request compares favorably to thefunctionality template. Such a determination may be based on one or moreof the payload, a payload analysis, and a comparison of the payloadanalysis to the functionality template. For example, the processingmodule determines that the request compares favorably to thefunctionality template when the processing module determines that aregistry value of the payload does not conflict with a current registryvalue. As another example, the processing module determines that therequest compares favorably to the functionality template when thepayload is not a certificate authority certificate. As yet anotherexample, the processing module determines that the request comparesfavorably to the functionality template when an internet protocol (IP)address associated with a requester of the request does not compareunfavorably to an unfavorable IP address list.

The method branches to step 188 of FIG. 9D where the processing moduleretrieves a key share based on sharing function parameters when theprocessing module determines that the request compares favorably to thefunctionality template. The method continues to step 210 when theprocessing module determines that the request compares unfavorably tothe functionality template. The method continues at step 212 where theprocessing module outputs the request rejection message. The methodcontinues with the steps of FIG. 9D where the processing moduleretrieves the key share based on sharing function parameters, generatesa signature result based on the key share and message to sign, andoutputs the signature result.

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, text, graphics, audio, etc. any of which may generally bereferred to as ‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. For some industries, anindustry-accepted tolerance is less than one percent and, for otherindustries, the industry-accepted tolerance is 10 percent or more. Otherexamples of industry-accepted tolerance range from less than one percentto fifty percent. Industry-accepted tolerances correspond to, but arenot limited to, component values, integrated circuit process variations,temperature variations, rise and fall times, thermal noise, dimensions,signaling errors, dropped packets, temperatures, pressures, materialcompositions, and/or performance metrics. Within an industry, tolerancevariances of accepted tolerances may be more or less than a percentagelevel (e.g., dimension tolerance of less than +/−1%). Some relativitybetween items may range from a difference of less than a percentagelevel to a few percent. Other relativity between items may range from adifference of a few percent to magnitude of differences.

As may also be used herein, the term(s) “configured to”, “operablycoupled to”, “coupled to”, and/or “coupling” includes direct couplingbetween items and/or indirect coupling between items via an interveningitem (e.g., an item includes, but is not limited to, a component, anelement, a circuit, and/or a module) where, for an example of indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.

As may even further be used herein, the term “configured to”, “operableto”, “coupled to”, or “operably coupled to” indicates that an itemincludes one or more of power connections, input(s), output(s), etc., toperform, when activated, one or more its corresponding functions and mayfurther include inferred coupling to one or more other items. As maystill further be used herein, the term “associated with”, includesdirect and/or indirect coupling of separate items and/or one item beingembedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may be used herein, one or more claims may include, in a specificform of this generic form, the phrase “at least one of a, b, and c” orof this generic form “at least one of a, b, or c”, with more or lesselements than “a”, “b”, and “c”. In either phrasing, the phrases are tobe interpreted identically. In particular, “at least one of a, b, and c”is equivalent to “at least one of a, b, or c” and shall mean a, b,and/or c. As an example, it means: “a” only, “b” only, “c” only, “a” and“b”, “a” and “c”, “b” and “c”, and/or “a”, “b”, and “c”.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, “processing circuitry”, and/or “processing unit”may be a single processing device or a plurality of processing devices.Such a processing device may be a microprocessor, micro-controller,digital signal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, processing circuitry, and/or processing unitmay be, or further include, memory and/or an integrated memory element,which may be a single memory device, a plurality of memory devices,and/or embedded circuitry of another processing module, module,processing circuit, processing circuitry, and/or processing unit. Such amemory device may be a read-only memory, random access memory, volatilememory, non-volatile memory, static memory, dynamic memory, flashmemory, cache memory, and/or any device that stores digital information.Note that if the processing module, module, processing circuit,processing circuitry, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,processing circuitry and/or processing unit implements one or more ofits functions via a state machine, analog circuitry, digital circuitry,and/or logic circuitry, the memory and/or memory element storing thecorresponding operational instructions may be embedded within, orexternal to, the circuitry comprising the state machine, analogcircuitry, digital circuitry, and/or logic circuitry. Still further notethat, the memory element may store, and the processing module, module,processing circuit, processing circuitry and/or processing unitexecutes, hard coded and/or operational instructions corresponding to atleast some of the steps and/or functions illustrated in one or more ofthe Figures. Such a memory device or memory element can be included inan article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with one or more other routines. In addition, a flow diagrammay include an “end” and/or “continue” indication. The “end” and/or“continue” indications reflect that the steps presented can end asdescribed and shown or optionally be incorporated in or otherwise usedin conjunction with one or more other routines. In this context, “start”indicates the beginning of the first step presented and may be precededby other activities not specifically shown. Further, the “continue”indication reflects that the steps presented may be performed multipletimes and/or may be succeeded by other activities not specificallyshown. Further, while a flow diagram indicates a particular ordering ofsteps, other orderings are likewise possible provided that theprinciples of causality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form asolid-state memory, a hard drive memory, cloud memory, thumb drive,server memory, computing device memory, and/or other physical medium forstoring digital information.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method comprises: receiving, by a storagenetwork processing module, a write request for an encoded data slice ofa set of encoded data slices, wherein data is dispersed error encoded inaccordance with dispersed error encoding parameters to produce a set ofencoded data slices; generating, by the storage network processingmodule, parity data for the encoded data slice; sending, by the storagenetwork processing module, the encoded data slice to a first storageunit of a set of storage units; and sending, by the storage networkprocessing module, the parity data for the encoded data slice to asecond storage unit of the set of storage units.
 2. The method of claim1, further comprises: receiving, by a storage network processing module,a write update request for the encoded data slice; updating, by thestorage network processing module, the encoded data slice to produce anupdated encoded data slice; generating, by the storage networkprocessing module, parity data for the updated encoded data slice; andsending, by the storage network processing module, the parity data forthe updated encoded data slice to a third storage unit of a set ofstorage units.
 3. The method of claim 1, further comprises: receiving,by a storage network processing module, a write update request for theencoded data slice; updating, by the storage network processing module,the encoded data slice to produce an updated encoded data slice;generating, by the storage network processing module, delta parity datafor the updated encoded data slice; and sending, by the storage networkprocessing module, the parity data for the updated encoded data slice toa third storage unit of a set of storage units.
 4. The method of claim1, further comprising: receiving, by the storage network processingmodule, a write request for another encoded data slice of the set ofencoded data slices; generating, by the storage network processingmodule, parity data for the another encoded data slice; transmitting, bythe storage network processing module, the another encoded data slice toa third storage unit of the set of storage units; and transmitting, bythe storage network processing module, the parity data for the anotherencoded data slice to a fourth storage unit of the set of storage units.5. The method of claim 1, further comprising: updating, by the storagenetwork processing module, parity information of an encoded data sliceof at least one other encoded data slice of the set of encoded dataslices, wherein the updating is based on a corresponding one parity datato produce an encoded data slice that includes updated parity data. 6.The method of claim 1, wherein data is segmented into a plurality ofdata segments before the data is dispersed error encoded, wherein eachdata segment of the plurality of data segments is dispersed errorencoded in accordance with dispersed error encoding parameters toproduce a set of encoded data slices.
 7. The method of claim 1, furthercomprises: receiving, by a storage network processing module, deltaparity data for the encoded data slice; retrieving, by the storagenetwork processing module, the parity data for the encoded data slice;generating, by the storage network processing module, based on the deltaparity data and the parity data, updated parity data for the encodeddata slice; and sending, by the storage network processing module, theparity data for the updated encoded data slice to a third storage unitof a set of storage units.
 8. A method comprises: receiving, by astorage network processing module, a write request for an encoded dataslice of a set of encoded data slices, wherein data is encoded inaccordance with a dispersed storage error coding function to produce aset of encoded data slices; generating, by the storage networkprocessing module, a parity slice for each encoded data slice of the setof encoded data slices to produce a plurality of parity slices;transmitting, by the storage network processing module, a writethreshold number of encoded data slices of the set of encoded dataslices to a first set of storage units; and transmitting, by the storagenetwork processing module, the plurality of parity slices to a secondset of storage units.
 9. The method of claim 8, further comprises:receiving, by the storage network processing module, a write updaterequest for an encoded data slice of the set of encoded data slices;updating, by the storage network processing module, the encoded dataslice to produce an updated encoded data slice; generating, by thestorage network processing module, an parity slice for the updatedencoded data slice; and sending, by the storage network processingmodule, the parity slice for the updated encoded data slice to a thirdset of storage units.
 10. The method of claim 8, further comprises:receiving, by the storage network processing module, a write updaterequest for an encoded data slice of the set of encoded data slices;updating, by the storage network processing module, the encoded dataslice to produce an updated encoded data slice; generating, by thestorage network processing module, a delta parity slice for the updatedencoded data slice; and sending, by the storage network processingmodule, the delta parity slice for the updated encoded data slice to athird set of storage units.
 11. The method of claim 8, furthercomprising: updating, by the storage network processing module, a parityslice of an associated encoded data slice of at least one other encodeddata slice of the set of encoded data slices, wherein the updating isbased on a corresponding one parity slice to produce an encoded dataslice that includes updated parity data.
 12. The method of claim 8,wherein data is segmented into a plurality of data segments before thedata is dispersed error encoded, wherein each data segment of theplurality of data segments is dispersed error encoded in accordance withdispersed error encoding parameters to produce a set of encoded dataslices.
 13. The method of claim 8, further comprises: receiving, by astorage network processing module, delta parity data for an encoded dataslice of the set of encoded data slices; retrieving, by the storagenetwork processing module, the parity slice associated with the encodeddata slice; generating, by the storage network processing module, basedon the delta parity data and the parity slice, an updated parity slicefor the encoded data slice; and sending, by the storage networkprocessing module, the updated parity slice for the updated encoded dataslice to a third set of storage units.
 14. A method comprises:receiving, by a storage unit of a storage network, a write request foran parity slice of a plurality of parity slices, wherein data is encodedin accordance with a dispersed storage error coding function to producea set of encoded data slices, wherein a plurality of parity slices aregenerated from the set of encoded data slices; storing, by the storageunit, the parity slice in a memory unit associated with the storageunit; receiving, by the storage unit, an updated parity slice for theencoded data parity slice; and replacing, by the storage unit, theparity slice in the memory unit with the updated encoded data parityslice.
 15. The method of claim 14, further comprises: receiving, by thestorage unit, delta parity data for the parity slice retrieving, by thestorage unit, the parity slice; generating, by the storage unit, basedon the delta parity data and the parity slice, an updated parity slicefor the encoded data slice; and storing, by the storage unit, the parityslice in another memory unit associated with the storage unit.
 16. Themethod of claim 14, further comprises: receiving, by the storage unit, awrite update request for an encoded data slice associated with theparity slice; generating, by the storage unit, an updated parity slicefor the updated encoded data slice; and storing, by the storage unit,the updated parity slice in another memory unit associated with thestorage unit.
 17. The method of claim 14, further comprises: receiving,by the storage unit, delta parity data for the parity slice; retrievingthe parity slice; generating, by the storage unit, based on the deltaparity data and the parity slice, an updated parity slice; and storing,by the storage unit, the updated parity slice in another memory unitassociated with the storage unit.
 18. The method of claim 14, whereindata is segmented into a plurality of data segments before the data isdispersed error encoded, wherein each data segment of the plurality ofdata segments is dispersed error encoded in accordance with dispersederror encoding parameters to produce a set of encoded data slices.